The imaging of joints, (for example of the feet, knees, hips, and spinal column), is well known in the field of medical diagnosis for the purpose of being able to establish the presence of various pathological states. It has also been proposed to record images of such joints in a weight-loaded state, e.g., in order to be able to ascertain musculoskeletal defects. It has been found that joint parameters, such as the distances and orientation of joint components relative to each other differ between a standing position, e.g. a fully loaded position, and a lying position, e.g. an unloaded position. In this connection, see, for example, the article by Anna Hirschmann et al., Eur Radiol (2014) 24:553-558.
The recording of two-dimensional radiography images using an X-ray apparatus in the loaded states of joints is already known in the prior art. Moreover, dedicated imaging apparatuses for the limbs have been proposed which permit 3D imaging of joints of the feet and knees, also with the patient standing, as a loading state. Moreover, new kinds of robot-based X-ray systems have been proposed to allow images of joints over a greater area of the body, for example, including the hips and spinal column.
Three-dimensional imaging in loading states may simplify diagnosis by comparison with 2D imaging. For example, it is possible to record a three-dimensional image data set of a patient lying down (e.g., minimal loading of the joint) and a three-dimensional image data set of a patient standing up (e.g., maximal loading of the joint) using dedicated X-ray systems. However, three-dimensional images in loading states that lie between these extremes are not presently supported by imaging protocols. In the prior art, it has already been proposed to use devices that simulate varying loads in a supine position of the patient. However, it was found that loading of a joint in a supine position does not lead to the same effect as loading of the joint in an upright position.
Another fundamental problem in assessing image data sets of a joint that are recorded in loading states entails, especially in two-dimensional image data sets, the correct extraction of the required information from the image data, since the correct viewing angle and the correct viewing position are not necessarily guaranteed. Moreover, it is difficult to establish correspondences between different loading states.